> ## Documentation Index
> Fetch the complete documentation index at: https://www.landbase.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Analyze Patterns

> Surface what a set of accounts have in common — industries, keywords, tech stack, size patterns.

<div id="breadcrumb-wrapper" />

<div
  style={{display: 'none'}}
  data-related-resources={JSON.stringify([
{ title: 'Scout Lookalikes', href: '/reference/tools/scout-lookalikes' },
{ title: 'Expand Lookalikes', href: '/reference/tools/expand-lookalikes' },
{ title: 'Tools overview', href: '/reference/tools' }
])}
  id="page-related-resources"
/>

# Analyze Patterns

<div className="blog-post-content">
  "What do these 50 companies have in common?"

  Give Analyze Patterns a set of company websites and it tells you the most common values across them — industries, keywords, technologies, size ranges, locations. This is how you reverse-engineer an ICP from a set of accounts instead of guessing.

  ## How it works

  Provide a set of company websites. The system runs frequency analysis across all specified fields and returns the most common values with counts. It supports nested data structures, so it can analyze keywords, technologies, and any other structured field in the company schema — not just top-level firmographics.

  ## When to use it

  * **Before building a TAM** — drop in your 10 best customers, see what patterns emerge, use those patterns to define search criteria
  * **After a lookalike expansion** — check whether the expanded set actually shares the characteristics you expected
  * **Competitive analysis** — analyze a competitor's customer list to understand what market they're serving

  ## What you can analyze

  Any field in the company schema, including:

  * Industries
  * Keywords and description terms
  * Technologies used
  * Size ranges
  * Headquarters locations
  * And any other structured field

  Results are sorted by frequency — the most common values appear first, with counts showing how many of your input companies share each value.
</div>
